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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Protorheology in practice: Avoiding misinterpretation

Protorheology is the paradigm that any observed flow or deformation is a chance to infer quantitative rheological properties. While this creates many opportunities for insight, there is significant risk of misunderstanding the physics involved, e.g. misinterpreting a liquid as a solid or mistaking viscous flow time as viscoelastic relaxation time. We describe these and other potential mistakes, use case studies to show how serious the problems can be, and contrast misinterpretations with correct approaches and interpretations. Some issues are especially important with materials involving colloidal particles and flows involving surface tension. Whether the reader is making inference from a tilted vial, time-lapse gravity-driven flow, a bounce test, die swell, or any other protorheology observation, the examples here serve as a guide for avoiding bad data in protorheology.

42 ENGINEERING↗
DOE OSTI2020

Reaction mechanisms of a cyclic ether intermediate: Ethyloxirane

Oxiranes are a class of cyclic ethers formed in abundance during low-temperature combustion of hydrocarbons and biofuels, either via chain-propagating steps that occur from unimolecular decomposition of β -hydroperoxyalkyl radicals ( β -˙QOOH) or from reactions of HOÓ with alkenes. Ethyloxirane is one of four alkyl-substituted cyclic ether isomers produced as an intermediate from n -butane oxidation. While rate coefficients for β -˙QOOH → ethyloxirane + ÓH are reported extensively, subsequent reaction mechanisms of the cyclic ether are not. As a result, chemical kinetics mechanisms commonly adopt simplified chemistry to describe ethyloxirane consumption by convoluting several elementary reactions into a single step, which may introduce mechanism truncation error—uncertainty derived from missing or incomplete chemistry. Here we provide fundamental insight on reaction mechanisms of ethyloxirane in support of ongoing efforts to minimize mechanism truncation error. Reaction mechanisms are inferred from the detection of products during chlorine atom-initiated oxidation experiments using multiplexed photoionization mass spectrometry conducted at 10 Torr and temperatures of 650 K and 800 K. To complement the experiments, calculations of stationary point energies were conducted using the ccCA-PS3 composite method on ˙R + O 2 potential energy surfaces for the four ethyloxiranyl radical isomers, which produced barrier heights for 24 reaction pathways. In addition to products from ˙QOOH → cyclic ether + ÓH and ˙R + O 2 → conjugate alkene + HOÓ, both of which were significant pathways and are prototypical to alkane oxidation, other species were identified from ring-opening of both ethyloxiranyl and ˙QOOH radicals. The latter occurs when the unpaired electron is localized on the ether group, causing the initial ˙QOOH structure to ring-open and form a resonance-stabilized ketohydroperoxide-type radical. The present work provides the first analysis of ethyloxirane oxidation chemistry, which reveals that consumption pathways are complex and may require an expansion of submechanisms to increase the fidelity of chemical kinetics mechanisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Isomer-Dependent Reaction Mechanisms of Cyclic Ether Intermediates: cis -23-Dimethyloxirane and trans -23-Dimethyloxirane.

Oxiranes are a class of cyclic ethers formed in abundance during low-temperature combustion of hydrocarbons and biofuels, either via chain-propagating steps that occur from unimolecular decomposition of β-hydroperoxyalkyl radicals (β-˙QOOH) or from reactions of HÒO with alkenes. The cis- and trans-isomers of 2,3-dimethyloxirane are intermediates of n-butane oxidation, and while rate coefficients for β-˙QOOH → 2,3-dimethyloxirane + OH are reported extensively, subsequent reaction mechanisms of the cyclic ethers are not. As a result, chemical kinetics mechanisms commonly adopt simplified chemistry to describe the consumption of 2,3-dimethyloxirane by convoluting several elementary reactions into a single step, which may introduce mechanism truncation error—uncertainty derived from missing or incomplete chemistry. The present research examines the isomerdependence of 2,3-dimethyloxirane reaction mechanisms in support of ongoing efforts to minimize mechanism truncation error. Reaction mechanisms are inferred via the detection of products from Cl-initiated oxidation of both cis-2,3-dimethyloxirane and trans-2,3-dimethyloxirane using multiplexed photoionization mass spectrometry (MPIMS). The experiments were conducted at 10 Torr and temperatures of 650 K and 800 K. To complement the experiments, the enthalpies of stationary points on the ˙R + O 2 surfaces were computed at the ccCA-PS3 level of theory. In total, 28 barrier heights were computed on the 2,3-dimethyloxiranylperoxy surfaces. Two notable aspects are low-lying pathways that form resonance-stabilized ketohydroperoxide-type radicals caused by ˙QOOH ring-opening when the unpaired electron is localized adjacent to the ether group, and cis-trans isomerization of ˙R and ˙QOOH radicals, via inversion, which enable reaction pathways otherwise restricted by stereochemistry. Several species were identified in the MPIMS experiments from ring opening of 2,3-dimethyloxiranyl radicals. Neither of the two conjugate alkene isomers prototypical of ˙R + O 2 reactions were detected. Products were also identified from decomposition of ketohydroperoxide-type radicals. The present work provides the first analysis of 2,3-dimethyloxirane oxidation chemistry and reveals that consumption pathways are complex and require the expansion of submechanisms in chemical kinetics mechanisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

A survey on degradation modeling, prognosis, and prognostics-driven maintenance in wind energy systems

Wind energy generation proliferated over the past decades, introducing unique challenges and opportunities for failure prediction, operation and maintenance. Decision-makers are continuously looking into new methods to infer failure mechanisms and behaviors of wind turbine components to detect and intervene in the failures before they happen. Evidently, degradation modeling and prognosis become engaging topics for researchers and practitioners to prevent catastrophic failures. Prognostics-driven approaches predict the time of failure for the components (e.g., predicting remaining useful life), which provides significant insights for scheduling of operations and maintenance activities. Integrating these prognostics-driven insights into wind farm operations and maintenance presents a substantial challenge, demanding careful consideration of numerous factors such as accessibility, crew routing, and spare part logistics. This study provides state-of-the-art review for degradation modeling, prognosis, and prognostics-driven maintenance techniques for wind energy systems. The discussed techniques align with the United Nations' sustainable development goals, in particular Goal 7 (Affordable and Clean Energy), by enhancing effectiveness and sustainability of wind energy operations. This work also showcases open research questions related to degradation modeling, prognosis, and prognostics-driven maintenance.

Altinpulluk, Nur Banu↗
DOE OSTI2023

On the Scaling and Growth Limit of Fluvial Dunes

Abstract Bedforms emerge in a variety of shapes and sizes when a granular erodible surface is subject to a strong enough shear flow, as observed in topographic data from submarine canyons, rivers, deserts, and planetary bodies. The two salient features of bedforms are the ability to collectively transport particles, and to generate form drag thus increasing flow resistance. These two mechanisms are in competition and contribute to force bedforms of increasing size migrating more slowly. In a dedicated large‐scale open channel flow facility, hierarchies of fluvial bedforms were generated and measured in equilibrium conditions. The corresponding scale‐dependent migration velocity and mass flux contributions were quantified in the wave number and frequency domains. Experimental results are paired with a validated set of theoretical models to demonstrate that ripples or dunes reach an equilibrium state when drag partitioning ensures high enough frictional drag to sustain the bedload transport of sediment, and low enough form drag to enable the migration of the largest bedform size. This mechanism is inferred to constrain the growth of bedforms when sediment supply is not the limiting factor.

58 GEOSCIENCES↗
DOE OSTI2023

Use of machine learning to analyze chemistry card sort tasks

Education researchers are deeply interested in understanding the way students organize their knowledge. Card sort tasks, which require students to group concepts, are one mechanism to infer a student’s organizational strategy. However, the limited resolution of card sort tasks means they necessarily miss some of the nuance in a student’s strategy. Here in this work, we propose new machine learning strategies that leverage a potentially richer source of student thinking: free-form written language justifications associated with student sorts. Using data from a university chemistry card sort task, we use vectorized representations of language and unsupervised learning techniques to generate qualitatively interpretable clusters, which can provide unique insight in how students organize their knowledge. We compared these to machine learning analysis of the students’ sorts themselves. Machine learning-generated clusters revealed different organizational strategies than those built into the task; for example, sorts by difficulty or even discipline. There were also many more categories generated by machine learning for what we would identify as more novice-like sorts and justifications than originally built into the task, suggesting students’ organizational strategies converge when they become more expert-like. Finally, we learned that categories generated by machine learning for students’ justifications did not always match the categories for their sorts, and these cases highlight the need for future research on students’ organizational strategies, both manually and aided by machine learning. In sum, the use of machine learning to analyze results from a card sort task has helped us gain a more nuanced understanding of students’ expertise, and demonstrates a promising tool to add to existing analytic methods for card sorts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

From sequence to protein structure and conformational dynamics with artificial intelligence/machine learning

The 2024 Nobel Prize in Chemistry was awarded in part for de novo protein structure prediction using AlphaFold2, an artificial intelligence/machine learning (AI/ML) model trained on vast amounts of sequence and three-dimensional structure data. AlphaFold2 and related models, including RoseTTAFold and ESMFold, employ specialized neural network architectures driven by attention mechanisms to infer relationships between sequence and structure. At a fundamental level, these AI/ML models operate on the long-standing hypothesis that the structure of a protein is determined by its amino acid sequence. More recently, AlphaFold2 has been adapted for the prediction of multiple protein conformations by subsampling multiple sequence alignments. Herein, we provide an overview of the deterministic relationship between sequence and structure, which was hypothesized over half a century ago with profound implications for the biological sciences ever since. We postulate that protein conformational dynamics are also determined, at least in part, by amino acid sequence and that this relationship may be leveraged for construction of AI/ML models dedicated to predicting protein conformational ensembles. Accordingly, we describe a conceptual model architecture, which may be trained on sequence data in combination with conformationally sensitive structural information, coming primarily from nuclear magnetic resonance (NMR) spectroscopy. Notwithstanding certain limitations in this context, NMR offers abundant structural heterogeneity conducive to conformational ensemble prediction. As NMR and other data continue to accumulate, sequence-informed prediction of protein structural dynamics with AI/ML has the potential to emerge as a transformative capability across the biological sciences.

Artificial intelligence↗
DOE OSTI2023

Two-particle transverse momentum correlations in p p and p -Pb collisions at energies available at the CERN Large Hadron Collider

Two-particle transverse momentum differential correlators, recently measured in Pb-Pb collisions at energies available at the CERN Large Hadron Collider (LHC), provide an additional tool to gain insights into particle production mechanisms and infer transport properties, such as the ratio of shear viscosity to entropy density, of the medium created in Pb-Pb collisions. The longitudinal long-range correlations and the large azimuthal anisotropy measured at low transverse momenta in small collision systems, namely pp and p-Pb, at LHC energies resemble manifestations of collective behavior. This suggests that locally equilibrated matter may be produced in these small collision systems, similar to what is observed in Pb-Pb collisions. In this work, the same two-particle transverse momentum differential correlators are exploited in pp and p-Pb collisions at $\sqrt{s}$ = 7 TeV and $\sqrt{s_{NN}}$ = 5.02 TeV, respectively, to seek evidence for viscous effects. Specifically, the strength and shape of the correlators are studied as a function of the produced particle multiplicity to identify evidence for longitudinal broadening that might reveal the presence of viscous effects in these smaller systems. The measured correlators and their evolution from pp and p-Pb to Pb-Pb collisions are additionally compared to predictions from Monte Carlo event generators, and the potential presence of viscous effects is discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Characterization of Quantum Frequency Processors

Frequency-bin qubits possess unique synergies with wavelength-multiplexed lightwave communications, suggesting valuable opportunities for quantum networking with the existing fiber-optic infrastructure. Although the coherent manipulation of frequency-bin states requires highly controllable multi-spectral-mode interference, the quantum frequency processor (QFP) provides a scalable path for gate synthesis leveraging standard telecom components. Here, we summarize the state of the art in experimental QFP characterization. Distinguishing between physically motivated “open box” approaches that treat the QFP as a multiport interferometer, and “black box” approaches that view the QFP as a general quantum operation, we highlight the assumptions and results of multiple techniques, including quantum process tomography of a tunable beamsplitter—to our knowledge the first full process tomography of any frequency-bin operation. Our findings should inform future characterization efforts as the QFP increasingly moves beyond proof-of-principle tabletop demonstrations toward integrated devices and deployed quantum networking experiments.

42 ENGINEERING↗
NASA NTRS1981

Mechanism of parallel electric fields inferred from observations

Data from various experiments of the Atmosphere Explorer satellites are analyzed to test their consistency with the model of single-particle linear acceleration through a static parallel potential drop. Theoretical current/voltage and energy flux/voltage relations are applied to the data to predict the densities of source current carriers above the acceleration region for upward Birkeland currents. Comparison of these model predictions with simultaneous electron data indicates that the observed field-aligned potential drops are consistent with direct acceleration in the absence of anomalous resistivity.

Yeh, H.-C.↗
NASA NTRS1986

Program for Experimentation With Expert Systems

CERBERUS is forward-chaining, knowledge-based system program useful for experimentation with expert systems. Inference-engine mechanism performs deductions according to user-supplied rule set. Information stored in intermediate area, and user interrogated only when no applicable data found in storage. Each assertion posed by CERBERUS answered with certainty ranging from 0 to 100 percent. Rule processor stops investigating applicable rules when goal reaches certainty of 95 percent or higher. Capable of operating for wide variety of domains. Sample rule files included for animal identification, pixel classification in image processing, and rudimentary car repair for novice mechanic. User supplies set of end goals or actions. System complexity decided by user's rule file. CERBERUS written in FORTRAN 77.

Engle, S. W.↗
NASA NTRS1987

Precipitation factors leading to arc cloud formation

The combined efforts of three graduate students and the principal investigator are presented. Satellite observations and interpretation have become increasingly important in the areas of weather research and operational forecasting. One reason is that geostationary satellite imagery is the only meteorological observing tool that can follow the evolution of clouds from the synoptic scale down to the cumulas scale. Therefore, it can depict atmospheric activity which is up to two orders of magnitude smaller than can be resolved by conventional meteorological observations. This unique ability of the satellite provides the meteorologist a mechanism to infer weather events down to the mesoscale. This evolution is the subject of this report.

Brundidge, Kenneth C.↗
NASA NTRS1992

Knowledge representation requirements for model sharing between model-based reasoning and simulation in process flow domains

The paper examines the requirements for the reuse of computational models employed in model-based reasoning (MBR) to support automated inference about mechanisms. Areas in which the theory of MBR is not yet completely adequate for using the information that simulations can yield are identified, and recent work in these areas is reviewed. It is argued that using MBR along with simulations forces the use of specific fault models. Fault models are used so that a particular fault can be instantiated into the model and run. This in turn implies that the component specification language needs to be capable of encoding any fault that might need to be sensed or diagnosed. It also means that the simulation code must anticipate all these faults at the component level.

Throop, David R.↗
NASA NTRS2011

Spatial Distribution of Volcanic Hotspots and Paterae on Io: Implications for Tidal Heating Models and Magmatic Pathways

Io, the innermost of Jupiter's Galilean satellites, is the most volcanically active body in the Solar. System. Io's global mean heat flow is approximately 2 W/square m, which is approximately 20 times larger than on Earth. High surface temperatures concentrate within "hotspots" and, to date, 172 Ionian hotspots have been identified by spacecraft and Earth-based telescopes. The Laplace resonance between Io, Europa, and Ganymede maintains these satellites in noncircular orbits and causes displacement of their tidal bulges as the overhead position of Jupiter changes for each moon. Gravitational interactions between Jupiter and Io dominate the orbital evolution of the Laplacian system and generate enormous heat within to as tidal energy is dissipated. If this energy were transferred out of Io at the same rate as it is generated, then the associated surface heat flux would be 2.24 +/- 0.45 W/square m. This estimate is in good agreement with observed global heat flow, but to better constrain tidal dissipation mechanisms and infer how thermal energy is transferred to Io's surface, it is critical to closely examine the spatial distribution of volcanic features. End-member tidal dissipation models either consider that heating occurs completely in the mantle, or completely in the asthenosphere. Mixed models typically favor one-third mantle and two-thirds asthenosphere heating. Recent models also consider the effects of mantle-asthenosphere boundary permeability and asthenospheric instabilities. Deep-mantle heating models predict maximum surface heat flux near the poles, whereas asthenosphere heating models predict maxima near the equator-particularly in the Sub-Jovian and Anti-Jovian hemispheres, with smaller maxima occurring at orbit tangent longitudes. Previous studies have examined the global distribution of Ionian hotspots and patera (i.e., irregular or complex craters with scalloped edges that are generally interpreted to be volcanic calderas), but in this study, we combine a new geospatial analysis technique with an improved hotspot and paterae database .

Hamilton, C. W.↗
NASA NTRS2004

Windows(Registered Trademark)-Based Software Models Cyclic Oxidation Behavior

Oxidation of high-temperature aerospace materials is a universal issue for combustion-path components in turbine or rocket engines. In addition to the question of the consumption of material due to growth of protective scale at use temperatures, there is also the question of cyclic effects and spallation of scale on cooldown. The spallation results in the removal of part of the protective oxide in a discontinuous step and thereby opens the way for more rapid oxidation upon reheating. In experiments, cyclic oxidation behavior is most commonly characterized by measuring changes in weight during extended time intervals that include hundreds or thousands of heating and cooling cycles. Weight gains occurring during isothermal scale-growth processes have been well characterized as being parabolic or nearly parabolic functions of time because diffusion controls reaction rates. In contrast, the net weight change in cyclic oxidation is the sum of the effects of the growth and spallation of scale. Typically, the net weight gain in cyclic oxidation is determined only empirically (that is, by measurement), with no unique or straightforward mathematical connection to either the rate of growth or the amount of metal consumed. Thus, there is a need for mathematical modeling to infer spallation mechanisms. COSP is a computer program that models the growth and spallation processes of cyclic oxidation on the basis of a few elementary assumptions that were discussed in COSP: A Computer Model of Cyclic Oxidation, Oxidation of Metals, vol. 36, numbers 1 and 2, 1991, pages 81-112. Inputs to the model include the selection of an oxidation-growth law and a spalling geometry, plus oxide-phase, growth-rate, cycle-duration, and spall-constant parameters. (The spalling fraction is often shown to be a constant factor times the existing amount of scale.) The output of COSP includes the net change in weight, the amounts of retained and spalled oxide, the total amounts of oxygen and metal consumed, and the terminal rates of weight loss and metal consumption.

Smialek, J. L.↗
DOE OSTI2026

In-Situ TEM Molten Salt Corrosion

Molten salt reactors (MSRs) offer a compelling pathway for next-generation nuclear energy, with advantages in thermal efficiency, inherent safety, and flexible fuel management. Yet, halide-based molten salts introduce significant materials challenges, particularly alloy corrosion. Alloy performance in these environments ultimately depends on understanding how corrosion initiates and progresses at the nanoscale, however most existing models rely on post-exposure characterization, leaving degradation mechanisms largely inferred rather than directly observed. NiCr alloys have garnered interest in MSRs applications as the Ni-based matrix provides strength and creep resistance, while Cr content offers oxidation resistance in air. However, NiCr corrosion resistance in chloride salts has proven poor due to preferential chromium dissolution, the formation of Cr-depleted pathways, and grain-boundary attack. This work aims to directly visualize corrosion of Ni-20Cr exposed to LiCl-KCl using in-situ Transmission Electron Microscopy (TEM) to capture real-time microstructural evolution during corrosion. Experiments will be performed at ~800 °C under controlled pressure conditions while utilizing Energy-Dispersive X-ray Spectroscopy (EDS) to analyze elemental redistribution. Observation of chromium depletion fronts, associated surface restructuring, and localized chloride enrichment are expected. Ultimately, this study is expected to provide a link between microscale processes and the macroscopic degradation behaviors relevant to MSR operation in advanced reactor environments. Simultaneously, this approach enables future in-situ investigations regarding alloy composition, salt chemistry, and their influence on corrosion pathways and long-term stability.?

36 - MATERIALS SCIENCE↗